Predicting Environmental Impact of Hazardous Liquid Pipeline Accidents: Application of Intelligent Systems
Publication: Journal of Environmental Engineering
Volume 146, Issue 2
Abstract
In case of failure, hazardous liquid pipelines can have adverse environmental consequences. This study presents a method to predict the occurrence of certain environmental impacts resulting from hazardous liquid pipeline accidents. Explanatory variables, including pipe diameter, commodity transported, and incident area type, are used to train an adaptive neuro-fuzzy inference system (ANFIS). Three impact types are analyzed: water contamination, soil contamination, and impact on wildlife. Results show that the model can accurately predict whether a pipeline segment with given design characteristics could lead to adverse environmental impacts due to failure (14%, 6%, and 3% error for soil and water contamination and impact on wildlife, respectively). This model can be used in pipeline design and risk management planning to minimize the potential for environmental consequences. However, more comprehensive and robust reporting requirements beyond simple occurrence would improve our ability to prioritize these mitigative actions.
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Data Availability Statement
All data, models, or code generated or used during the study are available in a PHMSA repository online in accordance with funder data retention policies. They are available at https://www.phmsa.dot.gov/data-and-statistics/pipeline/gas-distribution-gas-gathering-gas-transmission-hazardous-liquids.
Acknowledgments
The authors acknowledge the contribution of Dr. Petr E. Komers, president of MSES, Inc., for his ongoing emotional, professional, and financial support.
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Published In
Journal of Environmental Engineering
Volume 146 • Issue 2 • February 2020
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This work is made available under the terms of the Creative Commons Attribution 4.0 International license, http://creativecommons.org/licenses/by/4.0/.
History
Received: Mar 13, 2019
Accepted: Jun 4, 2019
Published online: Nov 26, 2019
Published in print: Feb 1, 2020
Discussion open until: Apr 26, 2020
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